1. Ethics and Research Methods Objective: Student will understand the ethics and different research methods that Psychologists use. It is actually more exciting than it sounds! You will need to remember all this exciting stuff for IB Psychology. Do Now: Pick up new Module, and get out 1 st set of Notes.

2. Psychology is first and foremost a science. Thus, it is based in research, but why do we have to learn this stuff? Before we delve into how to do research, you should be aware of three hurdles(phenomenons) that tend to skew our logic.

3. Hindsight Bias The tendency to believe, after learning the outcome, that you knew it all along. Example: You didn’t study for an exam and you feel unsure about the results. When the results come back, you made a A. You brag to your friends, “I knew I’d aced that exam!” And you actually believe it in hindsight.

4. Overconfidence We tend to think we know more than we do. 82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety. 81% of new business owners felt they had an excellent chance of their businesses succeeding. When asked about the success of their peers, the answer was only 39%. (Now that's overconfidence!!!)

5. Confirmation bias When we selectively notice or focus upon evidence which tends to support the things we already believe to be or want to be true. For example: A student who is going to write a research paper may primarily search for information that would confirm his or her beliefs. The student may fail to search for or fully consider information that is inconsistent with his or her beliefs.

6. The Scientific Method - is a system for reducing bias and maintaining objectivity in the measurement of data. Use a step by step approach: 1. formulate the question – What you would like to find out? 2. develop a hypothesis 3. test the hypothesis – gather data somehow with a survey, observation, or do an experiment, and set up variables 4. draw conclusions – set up data in some statistical method and analyze if there is a cause and effect relationship or confounding variables 5. report our results/build a theory – so someone else can replicate your investigation, and rip it apart, thus a lot of debates in Psychology Past AP exams have required you to know the order and understanding of these steps.

7. Hypothesis Expresses a relationship between two variables. A variable is anything that can vary among participants in a study. For example: Participating in class leads to better grades than not participating in class.

8. Two types of research Applied Research has clear, practical applications. YOU CAN USE IT!!! Basic Research explores questions that you may be curious about, but not intended to be immediately used, but may be able to apply it later. Research on therapies for drug addicts has a clear purpose. Studying how kissing changes when you get older is interesting…but that’s about it.

9. What methods do researchers use to study behavior?

10. Non-experimental - Descriptive May use Naturalistic Observation Subjects are observed in their natural environment. The environment is not manipulated. Advantage is no Hawthorne effect. Disadvantages: can not really show cause and effect may have observer bias – expectations No control like in an experiment

11. Hawthorne Effect (observer effect) Just the fact that you know you are in an experiment can cause change. Most people want to help an experiment work. Whether the lights were brighter or dimmer, production went up in the Hawthorne electric plant.

12. Case Studies A detailed picture of one or a few subjects Advantage: Gives us a good deal amount of information Can take advantages of bad situation or disaster Disadvantage: May not even give us correlation data Observe only a few people but generalized to the public Sampling issues – may not really generalize to the public Observer bias An ideal case study is on people who have a little known disorder called Synesthesia- where someone’s senses are joined together, they can taste or see colors of the different months of the year.

13. Survey Method Most common way of collecting data for a study in psychology Cheap and fast Need a good random sample Low-response rate People Lie/Social desirability

14. Experimental Method Looking to determine - Cause and Effect Have more control than any other research method. But may not be like real life, lacks ecological validity. Smoking causes health issues.

15. Independent Variable Whatever is being manipulated in the experiment. Hopefully the independent variable brings about change. For Example: If there is a drug in an experiment, the drug is almost always the independent variable.

16. Dependent Variable For example: The dependent variable would be the effect of the drug. Whatever is being measured in the experiment. It is dependent on the independent variable. You must be able to measure the dependent variable.

17. Operational Definitions (OD) Explains what you mean in your hypothesis. How will the variables be measured in “real life” terms. How did you operationalize the variables? OD tells us if the study is valid and reliable, if someone can follow the OD and can repeat the experiment with the same results, then the experiment is reliable. For example: Let’s say your hypothesis is that chocolate causes violent behavior. What do you mean by chocolate? What do you mean by violent behavior?

18. How do researchers ensure findings are valid? Random assignment – process of assigning subjects into two groups randomly so that each has an equal chance of being in either group, helps control for confounding variables. Experimental Group – the group that is exposed to the independent variable Control Group – subjects in an experiment who are not exposed to the independent variable or may have been given a placebo. Group Matching - selecting equal number of males and females.

19. More Terminology Representation sample – randomly selected sample of subjects from a larger population of subjects. Population – the entire group of people in which the researcher is interested. Participants/subjects – people who are part of the study

20. Some other Hazards of an Experiment If you wanted to prove that smoking causes heart issues, what are some confounding variables? Lifestyle and family history may also effect the heart. Beware of Confounding Variables The object of an experiment is to prove that A causes B. A confounding variable is anything that could cause change in B, that is not A.

21. Other confounding variables Experimenter/Participant Bias/Effect- not a conscious act but may have expectations or try to help. To prevent bias use Double-Blind Procedure-when neither the experimenter nor the participant know who is getting the drug. The Placebo Effect - get better because you think you should Ethical issues of using a placebo

22. Correlational Method Correlation expresses a relationship between two variable by using a statistical technique that looks for patterns and relationships between variables. Variable – is anything that can change or vary, what is being measured. Used when it might be unethical to do an experiment.(i.e. the correlation between smoking and life expectancy is high) Correlation coefficient – a number derived from the formula for measuring a correlation and indicates the strength and direction of a correlation Disadvantage: Does not show causation just because two variable are related does not mean that one caused the other

23. Types of Correlation Positive Correlation The variables go in the SAME direction. Negative Correlation The variables go in opposite directions. Studying and grades hopefully has a positive correlation. Heroin use and grades probably has a negative correlation.

24. APA Ethical Guidelines for Research IRB- Internal Review Board Both for humans and animals.

25. Human Research Guidelines include the protections of participants’ rights and well-being Informed consent Justification when deception is used Right of participants to withdraw at any time Protection of participants from harm Confidentiality Debriefing.

26. Animal Research Must have a clear purpose Treated in a humane way Acquire animals legally Least amount of suffering possible.

27. Statistics Why??? Psychology base their conclusions on research finding. Data is collected using methods previous discussed and the results have to be analyzed. Statistics is the field that gives us the tools to do that. Objective: student will have an understanding of basic statistics to help them think critically about psychological research.

28. Descriptive and Inferential Statistics Psychologist have to do 2 things with the data they collect. First, they have to summarize the information, just describes sets of data – descriptive statistics. You might create a frequency distribution - Putting scores in order creates a frequency distribution and makes the raw data much more meaningful. Secondly, they make judgments and decisions about the data Do the groups differ or are they related? This is call Inferential statistics – if the difference between the data sets are greater than chance variation would predict. Statistics is the branch of math that is concerned with the collection and interpretation of data from samples.

29. Two Main Types of Descriptive Statistics Measures of Central Tendency – numbers that best represent the most typical score of a frequency distribution. Measures of Variability – measurement of the degree of differences within a distribution or how the scores are spread out.

30. Central Tendency Know each and how to calculate: Mean, Median and Mode. Watch out for extreme scores or outliers. $25,000-Pam $25,000- Kevin $25,000- Angela $100,000- Andy $100,000- Dwight $200,000- Jim $300,000- Michael Let’s look at the salaries of the employees at Dunder Mifflen Paper in Scranton: The median salary looks good at $100,000. The mean salary also looks good at about $110,000. But the mode salary is only $25,000. Maybe not the best place to work.

31. Measures of Variability How spread out the scores are from each other. The more the scores cluster around the central scores, the smaller the measure of variability and The more widely the sores differ from the central scores, the larger this measurement will be. Two ways to measure, the simpler method is by calculating range of the set of scores, or the difference between the highest score and the lowest score. Intelligence Scores for 10 people A 240F 100 B 105 G 100 C 103 H 100 D 103 I 98 E 102J 95 The range would be 240-95 or 145, but if you look there is not much variation except for one high score of 240, so this might not be a good measure.

32. Frequency Distribution A table or graph that shows how often different numbers or scores appear in a particular set of scores. One common graph is a histogram – that provides a visual way to look at data from a frequency distributions. A polygon is a line graph that can represent the data in a frequency distribution that allows the shape of the data to be easily viewed A frequency polygon are those line graphs that a skewed distributions in one direction or the other.

33. Normal Curve A frequency distribution where the mean, median and mode are all the same- a perfect bell shape

34. Normal Distribution- used for intelligence or average weight represented in the population

35. Distributions are not always normal! Outliers skew distributions. If group has one high score, the curve has a positive skew (contains more low scores), Ex. a lot of students fail a test, so the test may not be fair or too hard. If a group has a low outlier, the curve has a negative skew (contains more high scores), e.x. Test was too easy except for those who did not study or listen in class.

36. Scores A unit that measures the distance of one score from the mean. A positive z score means a number above the mean. A negative z score means a number below the mean.

37. Another measure of variability is Standard Deviation(SD) is a number that represents how far away the scores in a data set are from the mean. The formula for finding the SD looks complicated but follow the steps and it is easy? 1.Calculates the data set’s mean.(add all scores and divide by number of items) 2.Subtract the mean from each individual score to find out how much each differs from the mean. 3.Square each deviation score. 4.Add up all of the squares you calculated in step 3. 5.Divide the total you calculated in step 4 by the number of scores in the data set. 6.Find the square root of the number you calculated in step 5. This square root is the standard deviation. Normally, you do not have to figure this out on the AP Exam, but you will not be able to use a calculator either.

38. Other measures of variability Range: distance from highest to lowest scores. Standard Deviation: the variance of scores around the mean. The higher the variance or SD, the more spread out the distribution is. Do scientists want a big or small SD?

39. Correlation Coefficients A correlation is a measure of the relationship between two or more variables. The correlation coefficient represents the strength and direction of the relationship between variables. Data is entered into a mathematical formula, the result will either be positive or negative. If positive, the variables increase in the same direction.(if one goes up the other goes up) If negative, the variables have an opposite relationship. (if one goes up the other goes down) The strength of the relationship will be determined by the actual number itself. (range between +1.00 and -1.00) The closer the number is to 0 (means no relationship), the weaker the relationship. A correlation of +1.00 is a perfect positive and means there is probably an error in calculation. +.89 is a strong positive relationship and -.89 is an equally strong negative relationship.

40. Inferential Statistics In any analysis that compares two or more sets of data, there is always the possibility of error in the data, or the possibility that luck or chance played a role in the experiment. So, if the difference is large enough, they have to eliminate luck or chance by using inferential statistics. A statistical technique is done to determine if the data is statistically significant – larger than chance variation would predict. Some examples of these techniques,(T-tests, ANOVA or MANOVA) you only need to know how to do this if you take IB Psychology HL. In general, researchers are satisfied when theses test show a 95% likelihood that results are not by chance. (p <.05) chance is less than 5 out of 100. 5% likely the results are due to chance.

41. Validity and Reliability Reliability – the tendency of a test to produce the same scores again and again each time it is given to the same people, repeatable. Validity – the degree to which a test actually measures what it is supposed to measure.